Solution Architect Technology

Job Title

Principal Data Scientist / SLM Model Development Architect

Role Summary

The Principal Data Scientist / SLM Model Development Architect is a senior technical leadership role responsible for defining the architecture strategy and enterprise adoption of Small Language Models (SLMs) and advanced AI solutions. This role provides end-to-end ownership of model design optimization deployment and governance while mentoring teams and influencing AI strategy across the organization.

Educational Qualification

• ME / BE / MCA / PhD
• PhD preferred for advanced research and architectural leadership roles

Experience

• 10 years of experience in Data Science Machine Learning and Deep Learning
• Proven experience in architecting and deploying production-grade AI/ML systems at enterprise scale

Work Schedule

• Day Shift

Key Responsibilities

Architecture & Strategy

• Define and own the enterprise architecture standards and roadmap for Small Language Model (SLM) development.
• Design domain-specific SLMs optimized for accuracy latency cost and scalability.
• Drive architectural decisions for model selection fine-tuning compression and inference optimization.
• Ensure alignment of AI solutions with enterprise security compliance and governance requirements.

Advanced Model Development

• Lead the design development and deployment of ML DL and SLM-based solutions.
• Apply deep mathematical and statistical knowledge to optimize model performance.
• Demonstrate successful delivery of multiple production deployments with measurable business impact.
• Provide architectural oversight for traditional ML deep learning and NLP-based systems.

NLP & Language Modeling

• Architect and guide solutions involving NLP embeddings transformers and language models.
• Lead fine-tuning and adaptation of language models for domain-specific use cases.
• Establish best practices for prompt engineering evaluation metrics and performance monitoring.

Technical & Platform Leadership

• Provide technical authority in Python scientific computing and data processing frameworks.
• Guide teams on the effective use of TensorFlow PyTorch and Keras.
• Ensure high-quality analytical data access through complex and optimized SQL designs.
• Oversee development in Linux and GPU-based environments.

Cloud MLOps & Production Readiness

• Architect and govern ML/AI solutions on AWS or Azure platforms.
• Define and enforce MLOps standards including CI/CD model versioning monitoring and lifecycle management.
• Ensure reliability scalability and maintainability of AI systems in production.

Leadership & Mentorship

• Act as Principal Architect and technical mentor for Data Scientists and ML Engineers.
• Lead design reviews technical decision forums and architectural governance boards.
• Collaborate closely with product engineering security and compliance stakeholders.
• Drive innovation while ensuring delivery discipline in Agile environments.

Required Skills & Expertise

• Strong foundation in ML algorithms: Random Forest SVM Regression models Boosting & Bagging
• Deep learning expertise: CNN RNN LSTM GRU
• Advanced NLP and language model experience
• Expert-level Python programming
• Cloud-based ML architecture and deployment
• Enterprise AI governance and best practices

Preferred / Nice to Have

• Experience with Computer Vision cases
• Exposure to Responsible AI model risk management and regulatory compliance
• Experience defining AI strategy at an organizational or platform level

Role Level

• Principal / Architect
• Individual Contributor with enterprise-level technical leadership responsibilities

Required Experience:

Staff IC